Classification of species and color of finished wooden components

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Abstract

This thesis describes the use of computer vision and pattern recognition
technology in the design of an automatic system which can distinguish species and color of
finished wooden components. The system can identify three different species that are
stained with several different colors. This system includes a host computer, color video
cameras and fiber optic lights. This thesis describes texture and color features and a
hierarchical classification strategy used in this system. An algorithm for determining linear
and piecewise linear discriminant functions using the convex hull is introduced. The effect
of removing wood grain on texture and color identification is also considered. The
classification system developed in this thesis has been successfully tested in the laboratory
with a large number of samples.